Time complexity 3 – asymptotic notations

Big-oh(O), omega(Ω), theta(Θ). It sounds like some magical words, but it is just a math. So don’t be scared and I will show you what it means and how to deal with it.

First of all I would like to say that before you will read this post you should read this one and this one about time complexity of an algorithm and why it is so important for a developer to know this.

Let start with a big-oh

Big-oh is a upper bound of our algorithm function.

What does it mean?

Simply said, we have a function that describe complexity of algorithm and that function looks like this:

f(n) = 3n^2 + 2n + 1

then we have a another function that is upper bound for our function f(n):